{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "pycharm": {
     "is_executing": true,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as colors\n",
    "import os\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "\n",
    "from pandas import set_option\n",
    "set_option(\"display.max_rows\",10)\n",
    "set_option('display.width', 200)\n",
    "import seaborn as sns\n",
    "\n",
    "import math\n",
    "\n",
    "# import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "element_names = [\"孔隙度\",\"饱和度\",\"渗透率\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# 定义要输入的维度AC、CNL、DEN、GR、RD、RS\n",
    "# input_vectors = [\"AC\",\"CNL\",\"DEN\",\"GR\"]\n",
    "input_vectors = [\"AC\",\"CNL\",\"DEN\",\"GR\",\"RLLD\",\"RLLS\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# \"Cor-Relationship-xia-train.csv\"  ,'AB-TT1-4500m-5070m.csv' 'AB-TT1-4500m-5070m.csv''AB-J404-3960m-4240m.csv'\n",
    "train_data_path = '../data/train2/'\n",
    "filename_AB = '井数据2_20190718_训练_section_1and2-train.csv' # '井数据2_20190718_训练_section_1-train.csv'\n",
    "train_file_path = os.path.join(train_data_path,filename_AB)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# 待预测段的常规测井曲线\n",
    "test_data_path = '../data/test2/'\n",
    "filename_A = '井数据2_20190718_测试_section_1and2-test_nolabel.csv'\n",
    "test_file_path = os.path.join(test_data_path,filename_A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "HighRDataPath = '../data/testH/'\n",
    "filename_C_H = '井数据2_20190718_测试_section_1and2-test.csv'\n",
    "HighR_file_Path = os.path.join(HighRDataPath,filename_C_H)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# 查看训练集范围"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>深度</th>\n",
       "      <th>孔隙度</th>\n",
       "      <th>渗透率</th>\n",
       "      <th>饱和度</th>\n",
       "      <th>AC</th>\n",
       "      <th>SP</th>\n",
       "      <th>GR</th>\n",
       "      <th>CNL</th>\n",
       "      <th>DEN</th>\n",
       "      <th>RLLD</th>\n",
       "      <th>RLLS</th>\n",
       "      <th>PERM</th>\n",
       "      <th>POR</th>\n",
       "      <th>SH</th>\n",
       "      <th>SW</th>\n",
       "      <th>序号</th>\n",
       "      <th>子区</th>\n",
       "      <th>用途</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3650.310</td>\n",
       "      <td>5.850000</td>\n",
       "      <td>0.096000</td>\n",
       "      <td>68.760002</td>\n",
       "      <td>213.768</td>\n",
       "      <td>-40.377000</td>\n",
       "      <td>35.410</td>\n",
       "      <td>5.753</td>\n",
       "      <td>2.555</td>\n",
       "      <td>73.658</td>\n",
       "      <td>77.854</td>\n",
       "      <td>0.125932</td>\n",
       "      <td>6.319153</td>\n",
       "      <td>6.848655</td>\n",
       "      <td>53.970303</td>\n",
       "      <td>91</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3650.450</td>\n",
       "      <td>4.770000</td>\n",
       "      <td>0.151000</td>\n",
       "      <td>68.269997</td>\n",
       "      <td>203.032</td>\n",
       "      <td>-39.801000</td>\n",
       "      <td>36.794</td>\n",
       "      <td>4.889</td>\n",
       "      <td>2.542</td>\n",
       "      <td>128.933</td>\n",
       "      <td>128.810</td>\n",
       "      <td>0.030236</td>\n",
       "      <td>4.569192</td>\n",
       "      <td>7.387618</td>\n",
       "      <td>57.338078</td>\n",
       "      <td>91</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3650.600</td>\n",
       "      <td>6.130000</td>\n",
       "      <td>0.086000</td>\n",
       "      <td>66.830002</td>\n",
       "      <td>200.245</td>\n",
       "      <td>-39.374000</td>\n",
       "      <td>41.964</td>\n",
       "      <td>4.956</td>\n",
       "      <td>2.539</td>\n",
       "      <td>146.471</td>\n",
       "      <td>142.905</td>\n",
       "      <td>0.019073</td>\n",
       "      <td>4.114914</td>\n",
       "      <td>9.465652</td>\n",
       "      <td>60.048485</td>\n",
       "      <td>91</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3650.760</td>\n",
       "      <td>5.430000</td>\n",
       "      <td>0.052000</td>\n",
       "      <td>61.459999</td>\n",
       "      <td>200.506</td>\n",
       "      <td>-38.499000</td>\n",
       "      <td>49.643</td>\n",
       "      <td>5.483</td>\n",
       "      <td>2.555</td>\n",
       "      <td>135.537</td>\n",
       "      <td>132.841</td>\n",
       "      <td>0.019956</td>\n",
       "      <td>4.157457</td>\n",
       "      <td>12.749502</td>\n",
       "      <td>61.753070</td>\n",
       "      <td>91</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3650.950</td>\n",
       "      <td>3.870000</td>\n",
       "      <td>0.034000</td>\n",
       "      <td>60.930000</td>\n",
       "      <td>202.684</td>\n",
       "      <td>-36.444000</td>\n",
       "      <td>74.314</td>\n",
       "      <td>7.785</td>\n",
       "      <td>2.592</td>\n",
       "      <td>91.048</td>\n",
       "      <td>87.872</td>\n",
       "      <td>0.028619</td>\n",
       "      <td>4.512470</td>\n",
       "      <td>25.103680</td>\n",
       "      <td>69.133150</td>\n",
       "      <td>91</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>11633</th>\n",
       "      <td>3645.089</td>\n",
       "      <td>10.408996</td>\n",
       "      <td>0.425351</td>\n",
       "      <td>48.822350</td>\n",
       "      <td>243.476</td>\n",
       "      <td>47.239998</td>\n",
       "      <td>79.371</td>\n",
       "      <td>15.935</td>\n",
       "      <td>2.517</td>\n",
       "      <td>34.530</td>\n",
       "      <td>23.445</td>\n",
       "      <td>0.432192</td>\n",
       "      <td>9.531540</td>\n",
       "      <td>20.107590</td>\n",
       "      <td>40.471886</td>\n",
       "      <td>122</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11634</th>\n",
       "      <td>3645.389</td>\n",
       "      <td>8.769841</td>\n",
       "      <td>0.438441</td>\n",
       "      <td>54.557743</td>\n",
       "      <td>245.146</td>\n",
       "      <td>46.113000</td>\n",
       "      <td>84.880</td>\n",
       "      <td>16.438</td>\n",
       "      <td>2.471</td>\n",
       "      <td>44.497</td>\n",
       "      <td>30.530</td>\n",
       "      <td>0.489198</td>\n",
       "      <td>9.803748</td>\n",
       "      <td>22.997742</td>\n",
       "      <td>34.711130</td>\n",
       "      <td>122</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11635</th>\n",
       "      <td>3645.499</td>\n",
       "      <td>8.796296</td>\n",
       "      <td>0.465563</td>\n",
       "      <td>47.899944</td>\n",
       "      <td>244.508</td>\n",
       "      <td>45.549000</td>\n",
       "      <td>76.092</td>\n",
       "      <td>16.472</td>\n",
       "      <td>2.467</td>\n",
       "      <td>49.873</td>\n",
       "      <td>34.372</td>\n",
       "      <td>0.466774</td>\n",
       "      <td>9.699755</td>\n",
       "      <td>18.458242</td>\n",
       "      <td>33.120830</td>\n",
       "      <td>122</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11636</th>\n",
       "      <td>3645.779</td>\n",
       "      <td>11.063576</td>\n",
       "      <td>0.460750</td>\n",
       "      <td>40.755680</td>\n",
       "      <td>241.491</td>\n",
       "      <td>44.562000</td>\n",
       "      <td>49.060</td>\n",
       "      <td>15.613</td>\n",
       "      <td>2.465</td>\n",
       "      <td>57.739</td>\n",
       "      <td>39.196</td>\n",
       "      <td>0.371265</td>\n",
       "      <td>9.207986</td>\n",
       "      <td>6.662848</td>\n",
       "      <td>32.341908</td>\n",
       "      <td>122</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11637</th>\n",
       "      <td>3645.939</td>\n",
       "      <td>7.286730</td>\n",
       "      <td>0.384582</td>\n",
       "      <td>56.843586</td>\n",
       "      <td>238.794</td>\n",
       "      <td>43.995003</td>\n",
       "      <td>52.261</td>\n",
       "      <td>15.275</td>\n",
       "      <td>2.479</td>\n",
       "      <td>63.561</td>\n",
       "      <td>42.296</td>\n",
       "      <td>0.299367</td>\n",
       "      <td>8.768379</td>\n",
       "      <td>7.905800</td>\n",
       "      <td>32.291480</td>\n",
       "      <td>122</td>\n",
       "      <td>2</td>\n",
       "      <td>训练井</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11638 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             深度        孔隙度       渗透率        饱和度       AC         SP      GR     CNL    DEN     RLLD     RLLS      PERM       POR         SH         SW   序号  子区   用途\n",
       "0      3650.310   5.850000  0.096000  68.760002  213.768 -40.377000  35.410   5.753  2.555   73.658   77.854  0.125932  6.319153   6.848655  53.970303   91   2  训练井\n",
       "1      3650.450   4.770000  0.151000  68.269997  203.032 -39.801000  36.794   4.889  2.542  128.933  128.810  0.030236  4.569192   7.387618  57.338078   91   2  训练井\n",
       "2      3650.600   6.130000  0.086000  66.830002  200.245 -39.374000  41.964   4.956  2.539  146.471  142.905  0.019073  4.114914   9.465652  60.048485   91   2  训练井\n",
       "3      3650.760   5.430000  0.052000  61.459999  200.506 -38.499000  49.643   5.483  2.555  135.537  132.841  0.019956  4.157457  12.749502  61.753070   91   2  训练井\n",
       "4      3650.950   3.870000  0.034000  60.930000  202.684 -36.444000  74.314   7.785  2.592   91.048   87.872  0.028619  4.512470  25.103680  69.133150   91   2  训练井\n",
       "...         ...        ...       ...        ...      ...        ...     ...     ...    ...      ...      ...       ...       ...        ...        ...  ...  ..  ...\n",
       "11633  3645.089  10.408996  0.425351  48.822350  243.476  47.239998  79.371  15.935  2.517   34.530   23.445  0.432192  9.531540  20.107590  40.471886  122   2  训练井\n",
       "11634  3645.389   8.769841  0.438441  54.557743  245.146  46.113000  84.880  16.438  2.471   44.497   30.530  0.489198  9.803748  22.997742  34.711130  122   2  训练井\n",
       "11635  3645.499   8.796296  0.465563  47.899944  244.508  45.549000  76.092  16.472  2.467   49.873   34.372  0.466774  9.699755  18.458242  33.120830  122   2  训练井\n",
       "11636  3645.779  11.063576  0.460750  40.755680  241.491  44.562000  49.060  15.613  2.465   57.739   39.196  0.371265  9.207986   6.662848  32.341908  122   2  训练井\n",
       "11637  3645.939   7.286730  0.384582  56.843586  238.794  43.995003  52.261  15.275  2.479   63.561   42.296  0.299367  8.768379   7.905800  32.291480  122   2  训练井\n",
       "\n",
       "[11638 rows x 18 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读取A、B部分共有数据\n",
    "AB = pd.read_csv(train_file_path,engine='python',encoding='GBK')\n",
    "AB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X = AB.loc[:,input_vectors]\n",
    "Y = AB.loc[:, element_names]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "minX = np.min(X)\n",
    "maxX = np.max(X)\n",
    "minY = np.min(Y)\n",
    "maxY = np.max(Y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.252, 2538.6133)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "minX,maxX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0015744810225442, 345.4894104003906)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "minY,maxY"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# 查看测试集范围"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "AB_new = pd.read_csv(test_file_path,engine='python',encoding='GBK')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>深度</th>\n",
       "      <th>孔隙度</th>\n",
       "      <th>渗透率</th>\n",
       "      <th>饱和度</th>\n",
       "      <th>AC</th>\n",
       "      <th>SP</th>\n",
       "      <th>GR</th>\n",
       "      <th>CNL</th>\n",
       "      <th>DEN</th>\n",
       "      <th>RLLD</th>\n",
       "      <th>RLLS</th>\n",
       "      <th>PERM</th>\n",
       "      <th>POR</th>\n",
       "      <th>SH</th>\n",
       "      <th>SW</th>\n",
       "      <th>序号</th>\n",
       "      <th>子区</th>\n",
       "      <th>用途</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3507.423</td>\n",
       "      <td>10.57</td>\n",
       "      <td>0.352508</td>\n",
       "      <td>53.560001</td>\n",
       "      <td>222.569</td>\n",
       "      <td>84.538</td>\n",
       "      <td>72.092</td>\n",
       "      <td>13.371</td>\n",
       "      <td>2.533</td>\n",
       "      <td>18.543</td>\n",
       "      <td>20.539</td>\n",
       "      <td>0.130834</td>\n",
       "      <td>7.264711</td>\n",
       "      <td>11.591696</td>\n",
       "      <td>66.948326</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3507.543</td>\n",
       "      <td>8.69</td>\n",
       "      <td>0.748226</td>\n",
       "      <td>55.959999</td>\n",
       "      <td>224.542</td>\n",
       "      <td>83.642</td>\n",
       "      <td>65.739</td>\n",
       "      <td>12.384</td>\n",
       "      <td>2.524</td>\n",
       "      <td>20.702</td>\n",
       "      <td>23.081</td>\n",
       "      <td>0.158305</td>\n",
       "      <td>7.586309</td>\n",
       "      <td>10.237123</td>\n",
       "      <td>60.872660</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3507.864</td>\n",
       "      <td>10.85</td>\n",
       "      <td>0.537384</td>\n",
       "      <td>49.730000</td>\n",
       "      <td>236.819</td>\n",
       "      <td>80.682</td>\n",
       "      <td>32.406</td>\n",
       "      <td>10.825</td>\n",
       "      <td>2.466</td>\n",
       "      <td>21.709</td>\n",
       "      <td>24.244</td>\n",
       "      <td>0.443458</td>\n",
       "      <td>9.587449</td>\n",
       "      <td>6.096953</td>\n",
       "      <td>47.869780</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3508.003</td>\n",
       "      <td>11.17</td>\n",
       "      <td>0.110546</td>\n",
       "      <td>52.380001</td>\n",
       "      <td>238.895</td>\n",
       "      <td>79.697</td>\n",
       "      <td>27.229</td>\n",
       "      <td>10.310</td>\n",
       "      <td>2.449</td>\n",
       "      <td>21.506</td>\n",
       "      <td>23.931</td>\n",
       "      <td>0.516576</td>\n",
       "      <td>9.925837</td>\n",
       "      <td>5.531714</td>\n",
       "      <td>46.576546</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3508.153</td>\n",
       "      <td>5.83</td>\n",
       "      <td>0.225791</td>\n",
       "      <td>63.720001</td>\n",
       "      <td>239.522</td>\n",
       "      <td>78.787</td>\n",
       "      <td>25.723</td>\n",
       "      <td>9.968</td>\n",
       "      <td>2.438</td>\n",
       "      <td>21.803</td>\n",
       "      <td>24.091</td>\n",
       "      <td>0.540392</td>\n",
       "      <td>10.028037</td>\n",
       "      <td>4.882371</td>\n",
       "      <td>45.821980</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3959</th>\n",
       "      <td>3600.930</td>\n",
       "      <td>9.13</td>\n",
       "      <td>0.280221</td>\n",
       "      <td>59.869999</td>\n",
       "      <td>235.876</td>\n",
       "      <td>3.977</td>\n",
       "      <td>36.891</td>\n",
       "      <td>8.199</td>\n",
       "      <td>2.521</td>\n",
       "      <td>29.970</td>\n",
       "      <td>26.787</td>\n",
       "      <td>0.264137</td>\n",
       "      <td>7.477752</td>\n",
       "      <td>6.068574</td>\n",
       "      <td>54.705470</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3960</th>\n",
       "      <td>3601.180</td>\n",
       "      <td>7.12</td>\n",
       "      <td>0.213215</td>\n",
       "      <td>57.919998</td>\n",
       "      <td>235.607</td>\n",
       "      <td>4.339</td>\n",
       "      <td>47.403</td>\n",
       "      <td>9.610</td>\n",
       "      <td>2.539</td>\n",
       "      <td>26.792</td>\n",
       "      <td>24.004</td>\n",
       "      <td>0.257390</td>\n",
       "      <td>7.433903</td>\n",
       "      <td>10.391018</td>\n",
       "      <td>58.183258</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3961</th>\n",
       "      <td>3601.620</td>\n",
       "      <td>6.84</td>\n",
       "      <td>0.185508</td>\n",
       "      <td>59.680000</td>\n",
       "      <td>228.176</td>\n",
       "      <td>5.313</td>\n",
       "      <td>57.011</td>\n",
       "      <td>10.210</td>\n",
       "      <td>2.548</td>\n",
       "      <td>23.666</td>\n",
       "      <td>21.245</td>\n",
       "      <td>0.117687</td>\n",
       "      <td>6.222656</td>\n",
       "      <td>14.755241</td>\n",
       "      <td>73.302230</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3962</th>\n",
       "      <td>3601.740</td>\n",
       "      <td>8.11</td>\n",
       "      <td>0.292973</td>\n",
       "      <td>56.869999</td>\n",
       "      <td>231.243</td>\n",
       "      <td>5.529</td>\n",
       "      <td>54.637</td>\n",
       "      <td>10.246</td>\n",
       "      <td>2.543</td>\n",
       "      <td>24.234</td>\n",
       "      <td>21.805</td>\n",
       "      <td>0.165346</td>\n",
       "      <td>6.722575</td>\n",
       "      <td>13.637983</td>\n",
       "      <td>67.310875</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3963</th>\n",
       "      <td>3602.010</td>\n",
       "      <td>8.45</td>\n",
       "      <td>0.280221</td>\n",
       "      <td>55.900002</td>\n",
       "      <td>236.858</td>\n",
       "      <td>5.741</td>\n",
       "      <td>49.564</td>\n",
       "      <td>9.628</td>\n",
       "      <td>2.546</td>\n",
       "      <td>27.283</td>\n",
       "      <td>24.529</td>\n",
       "      <td>0.289935</td>\n",
       "      <td>7.637816</td>\n",
       "      <td>11.336733</td>\n",
       "      <td>56.193990</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3964 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            深度    孔隙度       渗透率        饱和度       AC      SP      GR     CNL    DEN    RLLD    RLLS      PERM        POR         SH         SW  序号  子区   用途\n",
       "0     3507.423  10.57  0.352508  53.560001  222.569  84.538  72.092  13.371  2.533  18.543  20.539  0.130834   7.264711  11.591696  66.948326  31   2  测试井\n",
       "1     3507.543   8.69  0.748226  55.959999  224.542  83.642  65.739  12.384  2.524  20.702  23.081  0.158305   7.586309  10.237123  60.872660  31   2  测试井\n",
       "2     3507.864  10.85  0.537384  49.730000  236.819  80.682  32.406  10.825  2.466  21.709  24.244  0.443458   9.587449   6.096953  47.869780  31   2  测试井\n",
       "3     3508.003  11.17  0.110546  52.380001  238.895  79.697  27.229  10.310  2.449  21.506  23.931  0.516576   9.925837   5.531714  46.576546  31   2  测试井\n",
       "4     3508.153   5.83  0.225791  63.720001  239.522  78.787  25.723   9.968  2.438  21.803  24.091  0.540392  10.028037   4.882371  45.821980  31   2  测试井\n",
       "...        ...    ...       ...        ...      ...     ...     ...     ...    ...     ...     ...       ...        ...        ...        ...  ..  ..  ...\n",
       "3959  3600.930   9.13  0.280221  59.869999  235.876   3.977  36.891   8.199  2.521  29.970  26.787  0.264137   7.477752   6.068574  54.705470  90   2  测试井\n",
       "3960  3601.180   7.12  0.213215  57.919998  235.607   4.339  47.403   9.610  2.539  26.792  24.004  0.257390   7.433903  10.391018  58.183258  90   2  测试井\n",
       "3961  3601.620   6.84  0.185508  59.680000  228.176   5.313  57.011  10.210  2.548  23.666  21.245  0.117687   6.222656  14.755241  73.302230  90   2  测试井\n",
       "3962  3601.740   8.11  0.292973  56.869999  231.243   5.529  54.637  10.246  2.543  24.234  21.805  0.165346   6.722575  13.637983  67.310875  90   2  测试井\n",
       "3963  3602.010   8.45  0.280221  55.900002  236.858   5.741  49.564   9.628  2.546  27.283  24.529  0.289935   7.637816  11.336733  56.193990  90   2  测试井\n",
       "\n",
       "[3964 rows x 18 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AB_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X_new = AB_new.loc[:,input_vectors]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "minX_new = np.min(X_new)\n",
    "maxX_new = np.max(X_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.3461446 364.7764\n"
     ]
    }
   ],
   "source": [
    "print(minX_new,maxX_new)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# 查看有标签数据集范围"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "AB_new = pd.read_csv(HighR_file_Path,engine='python',encoding='GBK')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>深度</th>\n",
       "      <th>孔隙度</th>\n",
       "      <th>渗透率</th>\n",
       "      <th>饱和度</th>\n",
       "      <th>AC</th>\n",
       "      <th>SP</th>\n",
       "      <th>GR</th>\n",
       "      <th>CNL</th>\n",
       "      <th>DEN</th>\n",
       "      <th>RLLD</th>\n",
       "      <th>RLLS</th>\n",
       "      <th>PERM</th>\n",
       "      <th>POR</th>\n",
       "      <th>SH</th>\n",
       "      <th>SW</th>\n",
       "      <th>序号</th>\n",
       "      <th>子区</th>\n",
       "      <th>用途</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3507.423</td>\n",
       "      <td>10.57</td>\n",
       "      <td>0.352508</td>\n",
       "      <td>53.560001</td>\n",
       "      <td>222.569</td>\n",
       "      <td>84.538</td>\n",
       "      <td>72.092</td>\n",
       "      <td>13.371</td>\n",
       "      <td>2.533</td>\n",
       "      <td>18.543</td>\n",
       "      <td>20.539</td>\n",
       "      <td>0.130834</td>\n",
       "      <td>7.264711</td>\n",
       "      <td>11.591696</td>\n",
       "      <td>66.948326</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3507.543</td>\n",
       "      <td>8.69</td>\n",
       "      <td>0.748226</td>\n",
       "      <td>55.959999</td>\n",
       "      <td>224.542</td>\n",
       "      <td>83.642</td>\n",
       "      <td>65.739</td>\n",
       "      <td>12.384</td>\n",
       "      <td>2.524</td>\n",
       "      <td>20.702</td>\n",
       "      <td>23.081</td>\n",
       "      <td>0.158305</td>\n",
       "      <td>7.586309</td>\n",
       "      <td>10.237123</td>\n",
       "      <td>60.872660</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3507.864</td>\n",
       "      <td>10.85</td>\n",
       "      <td>0.537384</td>\n",
       "      <td>49.730000</td>\n",
       "      <td>236.819</td>\n",
       "      <td>80.682</td>\n",
       "      <td>32.406</td>\n",
       "      <td>10.825</td>\n",
       "      <td>2.466</td>\n",
       "      <td>21.709</td>\n",
       "      <td>24.244</td>\n",
       "      <td>0.443458</td>\n",
       "      <td>9.587449</td>\n",
       "      <td>6.096953</td>\n",
       "      <td>47.869780</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3508.003</td>\n",
       "      <td>11.17</td>\n",
       "      <td>0.110546</td>\n",
       "      <td>52.380001</td>\n",
       "      <td>238.895</td>\n",
       "      <td>79.697</td>\n",
       "      <td>27.229</td>\n",
       "      <td>10.310</td>\n",
       "      <td>2.449</td>\n",
       "      <td>21.506</td>\n",
       "      <td>23.931</td>\n",
       "      <td>0.516576</td>\n",
       "      <td>9.925837</td>\n",
       "      <td>5.531714</td>\n",
       "      <td>46.576546</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3508.153</td>\n",
       "      <td>5.83</td>\n",
       "      <td>0.225791</td>\n",
       "      <td>63.720001</td>\n",
       "      <td>239.522</td>\n",
       "      <td>78.787</td>\n",
       "      <td>25.723</td>\n",
       "      <td>9.968</td>\n",
       "      <td>2.438</td>\n",
       "      <td>21.803</td>\n",
       "      <td>24.091</td>\n",
       "      <td>0.540392</td>\n",
       "      <td>10.028037</td>\n",
       "      <td>4.882371</td>\n",
       "      <td>45.821980</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3959</th>\n",
       "      <td>3600.930</td>\n",
       "      <td>9.13</td>\n",
       "      <td>0.280221</td>\n",
       "      <td>59.869999</td>\n",
       "      <td>235.876</td>\n",
       "      <td>3.977</td>\n",
       "      <td>36.891</td>\n",
       "      <td>8.199</td>\n",
       "      <td>2.521</td>\n",
       "      <td>29.970</td>\n",
       "      <td>26.787</td>\n",
       "      <td>0.264137</td>\n",
       "      <td>7.477752</td>\n",
       "      <td>6.068574</td>\n",
       "      <td>54.705470</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3960</th>\n",
       "      <td>3601.180</td>\n",
       "      <td>7.12</td>\n",
       "      <td>0.213215</td>\n",
       "      <td>57.919998</td>\n",
       "      <td>235.607</td>\n",
       "      <td>4.339</td>\n",
       "      <td>47.403</td>\n",
       "      <td>9.610</td>\n",
       "      <td>2.539</td>\n",
       "      <td>26.792</td>\n",
       "      <td>24.004</td>\n",
       "      <td>0.257390</td>\n",
       "      <td>7.433903</td>\n",
       "      <td>10.391018</td>\n",
       "      <td>58.183258</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3961</th>\n",
       "      <td>3601.620</td>\n",
       "      <td>6.84</td>\n",
       "      <td>0.185508</td>\n",
       "      <td>59.680000</td>\n",
       "      <td>228.176</td>\n",
       "      <td>5.313</td>\n",
       "      <td>57.011</td>\n",
       "      <td>10.210</td>\n",
       "      <td>2.548</td>\n",
       "      <td>23.666</td>\n",
       "      <td>21.245</td>\n",
       "      <td>0.117687</td>\n",
       "      <td>6.222656</td>\n",
       "      <td>14.755241</td>\n",
       "      <td>73.302230</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3962</th>\n",
       "      <td>3601.740</td>\n",
       "      <td>8.11</td>\n",
       "      <td>0.292973</td>\n",
       "      <td>56.869999</td>\n",
       "      <td>231.243</td>\n",
       "      <td>5.529</td>\n",
       "      <td>54.637</td>\n",
       "      <td>10.246</td>\n",
       "      <td>2.543</td>\n",
       "      <td>24.234</td>\n",
       "      <td>21.805</td>\n",
       "      <td>0.165346</td>\n",
       "      <td>6.722575</td>\n",
       "      <td>13.637983</td>\n",
       "      <td>67.310875</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3963</th>\n",
       "      <td>3602.010</td>\n",
       "      <td>8.45</td>\n",
       "      <td>0.280221</td>\n",
       "      <td>55.900002</td>\n",
       "      <td>236.858</td>\n",
       "      <td>5.741</td>\n",
       "      <td>49.564</td>\n",
       "      <td>9.628</td>\n",
       "      <td>2.546</td>\n",
       "      <td>27.283</td>\n",
       "      <td>24.529</td>\n",
       "      <td>0.289935</td>\n",
       "      <td>7.637816</td>\n",
       "      <td>11.336733</td>\n",
       "      <td>56.193990</td>\n",
       "      <td>90</td>\n",
       "      <td>2</td>\n",
       "      <td>测试井</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3964 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            深度    孔隙度       渗透率        饱和度       AC      SP      GR     CNL    DEN    RLLD    RLLS      PERM        POR         SH         SW  序号  子区   用途\n",
       "0     3507.423  10.57  0.352508  53.560001  222.569  84.538  72.092  13.371  2.533  18.543  20.539  0.130834   7.264711  11.591696  66.948326  31   2  测试井\n",
       "1     3507.543   8.69  0.748226  55.959999  224.542  83.642  65.739  12.384  2.524  20.702  23.081  0.158305   7.586309  10.237123  60.872660  31   2  测试井\n",
       "2     3507.864  10.85  0.537384  49.730000  236.819  80.682  32.406  10.825  2.466  21.709  24.244  0.443458   9.587449   6.096953  47.869780  31   2  测试井\n",
       "3     3508.003  11.17  0.110546  52.380001  238.895  79.697  27.229  10.310  2.449  21.506  23.931  0.516576   9.925837   5.531714  46.576546  31   2  测试井\n",
       "4     3508.153   5.83  0.225791  63.720001  239.522  78.787  25.723   9.968  2.438  21.803  24.091  0.540392  10.028037   4.882371  45.821980  31   2  测试井\n",
       "...        ...    ...       ...        ...      ...     ...     ...     ...    ...     ...     ...       ...        ...        ...        ...  ..  ..  ...\n",
       "3959  3600.930   9.13  0.280221  59.869999  235.876   3.977  36.891   8.199  2.521  29.970  26.787  0.264137   7.477752   6.068574  54.705470  90   2  测试井\n",
       "3960  3601.180   7.12  0.213215  57.919998  235.607   4.339  47.403   9.610  2.539  26.792  24.004  0.257390   7.433903  10.391018  58.183258  90   2  测试井\n",
       "3961  3601.620   6.84  0.185508  59.680000  228.176   5.313  57.011  10.210  2.548  23.666  21.245  0.117687   6.222656  14.755241  73.302230  90   2  测试井\n",
       "3962  3601.740   8.11  0.292973  56.869999  231.243   5.529  54.637  10.246  2.543  24.234  21.805  0.165346   6.722575  13.637983  67.310875  90   2  测试井\n",
       "3963  3602.010   8.45  0.280221  55.900002  236.858   5.741  49.564   9.628  2.546  27.283  24.529  0.289935   7.637816  11.336733  56.193990  90   2  测试井\n",
       "\n",
       "[3964 rows x 18 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AB_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "X_high_new = AB_new.loc[:,input_vectors]\n",
    "Y_high_new = AB_new.loc[:, element_names]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AC</th>\n",
       "      <th>CNL</th>\n",
       "      <th>DEN</th>\n",
       "      <th>GR</th>\n",
       "      <th>RLLD</th>\n",
       "      <th>RLLS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>222.569</td>\n",
       "      <td>13.371</td>\n",
       "      <td>2.533</td>\n",
       "      <td>72.092</td>\n",
       "      <td>18.543</td>\n",
       "      <td>20.539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>224.542</td>\n",
       "      <td>12.384</td>\n",
       "      <td>2.524</td>\n",
       "      <td>65.739</td>\n",
       "      <td>20.702</td>\n",
       "      <td>23.081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>236.819</td>\n",
       "      <td>10.825</td>\n",
       "      <td>2.466</td>\n",
       "      <td>32.406</td>\n",
       "      <td>21.709</td>\n",
       "      <td>24.244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>238.895</td>\n",
       "      <td>10.310</td>\n",
       "      <td>2.449</td>\n",
       "      <td>27.229</td>\n",
       "      <td>21.506</td>\n",
       "      <td>23.931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>239.522</td>\n",
       "      <td>9.968</td>\n",
       "      <td>2.438</td>\n",
       "      <td>25.723</td>\n",
       "      <td>21.803</td>\n",
       "      <td>24.091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3959</th>\n",
       "      <td>235.876</td>\n",
       "      <td>8.199</td>\n",
       "      <td>2.521</td>\n",
       "      <td>36.891</td>\n",
       "      <td>29.970</td>\n",
       "      <td>26.787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3960</th>\n",
       "      <td>235.607</td>\n",
       "      <td>9.610</td>\n",
       "      <td>2.539</td>\n",
       "      <td>47.403</td>\n",
       "      <td>26.792</td>\n",
       "      <td>24.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3961</th>\n",
       "      <td>228.176</td>\n",
       "      <td>10.210</td>\n",
       "      <td>2.548</td>\n",
       "      <td>57.011</td>\n",
       "      <td>23.666</td>\n",
       "      <td>21.245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3962</th>\n",
       "      <td>231.243</td>\n",
       "      <td>10.246</td>\n",
       "      <td>2.543</td>\n",
       "      <td>54.637</td>\n",
       "      <td>24.234</td>\n",
       "      <td>21.805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3963</th>\n",
       "      <td>236.858</td>\n",
       "      <td>9.628</td>\n",
       "      <td>2.546</td>\n",
       "      <td>49.564</td>\n",
       "      <td>27.283</td>\n",
       "      <td>24.529</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3964 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           AC     CNL    DEN      GR    RLLD    RLLS\n",
       "0     222.569  13.371  2.533  72.092  18.543  20.539\n",
       "1     224.542  12.384  2.524  65.739  20.702  23.081\n",
       "2     236.819  10.825  2.466  32.406  21.709  24.244\n",
       "3     238.895  10.310  2.449  27.229  21.506  23.931\n",
       "4     239.522   9.968  2.438  25.723  21.803  24.091\n",
       "...       ...     ...    ...     ...     ...     ...\n",
       "3959  235.876   8.199  2.521  36.891  29.970  26.787\n",
       "3960  235.607   9.610  2.539  47.403  26.792  24.004\n",
       "3961  228.176  10.210  2.548  57.011  23.666  21.245\n",
       "3962  231.243  10.246  2.543  54.637  24.234  21.805\n",
       "3963  236.858   9.628  2.546  49.564  27.283  24.529\n",
       "\n",
       "[3964 rows x 6 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_high_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "minX_high_new = np.min(X_high_new)\n",
    "maxX_high_new = np.max(X_high_new)\n",
    "minY_high_new = np.min(Y_high_new)\n",
    "maxY_high_new = np.max(Y_high_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.3461446 364.7764\n"
     ]
    }
   ],
   "source": [
    "print(minX_high_new,maxX_high_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0018690000288188 476.154541\n"
     ]
    }
   ],
   "source": [
    "print(minY_high_new,maxY_high_new)"
   ]
  }
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